Painful Neuropathic Disorders: An Analysis of the RéGie De L’Assurance Maladie du QuéBec Database
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Painful neuropathic disorders (PNDs) refer to neurological disorders involving nerves in which pain is a predominant symptom. In most cases, PNDs involve the peripheral nerves. Treatment of PNDs is likely to use large health care resources. However, little is known about the economic burden of PNDs in Canada. METHOD: The present study was performed using data from a random sample of patients covered by the Régie de l'Assurance Maladie du Quebec drug plan. Subjects with a diagnosis of a peripheral PND were identified. Comorbidities, pain-related medication use and resource utilization were compared between PND patients and control patients without PNDs matched for age and sex in a 1:1 ratio. RESULTS: A total of 4912 patients with PNDs were identified. A higher level of comorbidities was found in the PND group (Von Korff chronic disease score 3.91 versus 2.54; P<0.001). The proportion of users of pain-related medications was significantly higher in the PND cohort than in the control group (chi-squared; P<0.001). The average annual number of physician visits was also significantly higher in the PND group than in the control group (14.7 versus 6.4; P<0.001). From a health ministry perspective, costs of health care resources were significantly higher in the PND group (4,163 dollars versus 1,846 dollars; P<0.001). The proportion of potentially inappropriate medications was 34% among those 65 years of age or older. CONCLUSIONS: PNDs are associated with a higher level of comorbidities, higher medical resources utilization and higher health care costs than non-PND conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".